Learn about the HPE Intelligent Data Platform and the new IT realities it addresses. With digital transformation underway in many organizations, more dynamic business models are becoming the key to success. This means infrastructure modernization and the introduction of technologies such as solid state storage, artificial intelligence and machine learning, software-defined infrastructure, and the cloud. At the same time, it means IT infrastructure management becomes much more complex. Enter HPE’s Intelligent Data Platform. With comprehensive coverage and AI/ML-driven real-time optimization that enables intelligent management of the entire data life cycle, the HPE Intelligent Data Platform enables an organization to get the most out of its IT resources while also meeting its evolving needs over time.

Are you looking for information to help you with your artificial intelligence deep learning journey? This Deep Learning Dummies guide will help you understand what AI, deep learning and machine learning can mean for you and your organization.

Are you looking for information to help you with your artificial intelligence deep learning journey? This Deep Learning Dummies guide will help you understand what AI, deep learning and machine learning can mean for you and your organization.

AI applications and especially deep learning systems are extremely demanding and require powerful parallel processing capabilities. IDC research shows that, in terms of core capacity, a large gap between actual and required CPU capability will develop in the next several years.
IDC is seeing the worldwide market for accelerated servers grow to $25.6 billion in 2022, with a 31.6% CAGR. Indeed, this market is growing so fast that IDC is forecasting that by 2021,12% of worldwide server value will be from accelerated compute.
Download this IDC report to find out why organizations like yours will need to make decisions about replacing existing general-purpose hardware or supplementing it with hardware dedicated to AI-specific processing tasks.

Have you ever wished for an army of clones to do all your thankless tasks and chores? Well, that fantasy is becoming a reality—at least on the Internet. And while they may not be actual clones, bots have begun doing lots of digital dirty work.
Managing your relationship with bots—good and bad—has become an inherent part of doing business in a connected world. With more than half of online traffic initiated by autonomous programs, it’s clear that bots are a driving force of technological change, and they’re here to stay.¹
As bot technology, machine learning, and AI continue to evolve, so will the threats they pose. And while some bots are good, many are malicious—and the cybercriminals behind them are targeting your apps. Preparing your organization to deal with the impact of bots on your business is essential to developing a sustainable strategy that will enable you to grow as you adapt to the new bot-enabled world.

Skills shortages are keeping business leaders up at night.
In fact, nearly half of executives say this skills gap is a major concern for the future of their organization — yet only 3% are significantly increasing training budgets.
Why? Workplace learning is a difficult nut to crack. Organizations often struggle to reskill their adult workforces with hard skills because they’re taking the wrong approach.
In this white paper, we take a look at why soft skills are not only integral for the future of work, but why they’re actually necessary for developing hard skills too.
You’ll also learn:
? How soft skills can lead to dramatic shifts in how people think
? How soft skills improve our ability to learn
? The most important skill for the 21st century — and how it can boost learning by 30%
Discover why empowering your people with soft skills is critical to unlocking the future success of your business.
Download Now

Infosys has embarked on a transformational journey to reinvent the way it and its clients do business. Like our most visionary clients, Infosys' goal is to become a completely knowledge- and data-driven organization, with agility built into its DNA so that it can quickly sense changing business needs and continuously evolve in response.
But we are not there yet, and the road is challenging. We are envisioning Infosys to be a Live Enterprise powered by the Infosys Digital Platform. The vision with the digital platform is to provide everyone who uses it with a frictionless digital experience wherever they are in the world. Anytime, anywhere access will be completely scalable and secure, and will feature online and offline compatibility in a flawless, employee-centric manner.

Learning is critical to enabling business strategy, from onboarding new hires to developing future leaders, to educating channel partners and customers. This study, based on responses collected from 185 organizations between July and September 2013, looks at how organizations connect learning to business priorities, create development programs that impact every stage of the employee lifecycle and utilize technology to support learning initiatives. It also examines the business impact of building learning capability and running effective learning programs. Research conducted by Aberdeen Group and brought to you thanks to Skillsoft.

According to a recent study, e-learning is now the most widely used method for workplace training. But talent development is more than just a learning solution – it requires an organizational commitment to training and development. This e-book offers five practical ways HR professionals can use e-learning to build a successful talent development culture in their organization.

Artificial intelligence (AI) and machine learning (ML) are emerging technologies that will transform organizations faster than ever before. In the digital transformation era, success will be based on using analytics to discover the insights locked in the massive volume of data being generated today. Historically, these insights were discovered through manually intensive data analytics—but the amount of data continues to grow, as does the complexity of data. AI and ML are the latest tools for data scientists, enabling them to refine the data into value faster.

Learn about the HPE Intelligent Data Platform and the new IT realities it addresses. With digital transformation underway in many organizations, more dynamic business models are becoming the key to success. This means infrastructure modernization and the introduction of technologies such as solid state storage, artificial intelligence and machine learning, software-defined infrastructure, and the cloud. At the same time, it means IT infrastructure management becomes much more complex. Enter HPE’s Intelligent Data Platform. With comprehensive coverage and AI/ML-driven real-time optimization that enables intelligent management of the entire data life cycle, the HPE Intelligent Data Platform enables an organization to get the most out of its IT resources while also meeting its evolving needs over time.

Competitive advantage from analytics is changing, and for the better. For the first time in four years, MIT Sloan Management Review found an increasing ability to strategically innovate with analytics based on interviews with more than 2,600 practitioners and scholars globally.
Learn more about key findings, including:
Wider use of analytics, better knowledge of its benefits and greater focus on applications have reversed a trend on the benefits of analytics.
Return on investment for analytics stems from the governing and sharing of data throughout the organization.
Machine learning enables organizations to discover more insight from their data, allowing employees to focus on other critical responsibilities.

Although the phrase “next-generation platforms and analytics” can evoke images of machine learning, big data, Hadoop, and the Internet of things, most organizations are somewhere in between the technology vision and today’s reality of BI and dashboards. Next-generation platforms and analytics often mean simply pushing past reports and dashboards to more advanced forms of analytics, such as predictive analytics. Next-generation analytics might move your organization from visualization to big data visualization; from slicing and dicing data to predictive analytics; or to using more than just structured data for analysis.

What do these market-defining trends have in common?
· Analytics for all
· Analytics as competitive differentiator
· Internet of Things
· Artificial intelligence/Machine learning/Cognitive computing
· Real-time analytics/event management
They all rely on data – timely, accurate data delivered within an insightful context – to deliver value. The question is: who in the enterprise is most qualified and prepared to help deliver on the vision and values of the data-driven enterprise?
It’s going to take a special type of professional to deliver that value to enterprises. Organizations are seeking professionals to step forward and take the lead, provide guidance and lend expertise to move into the brave new world of digital. The move to digital and all that it entails – sophisticated data analytics, online customer engagement and digital process efficiency – requires, above all, the skills and knowledge associated with handling data and turning it into insights. The move to digital i

When augmenting the benefits package for your organization, it’s natural to focus on traditional perks that employees have come to
expect: PTO, health insurance, and maybe a tuition assistance credit here or there. But if you’re looking for creative and effective ways to stimulate employee engagement while also driving business results, you’ll want to consider the powerful impact of offering language-learning opportunities.
Where’s the connection? And how can you reproduce these benefits within your organization? This playbook offers a deeper look at why language learning has such a positive influence on employee engagement and business performance, as well as step-by-step instructions for implementing a language-learning program in your organization.

Explore this e-book to find out how blending formal and informal learning via collaboration can help your organization in the following areas:
Overcoming the Economics of Learning
Creating a Culture of Learning
Enhancing Employee Engagement

In today’s IT infrastructure, data security can no longer be treated as an afterthought, because billions
of dollars are lost each year to computer intrusions and data exposures. This issue is compounded by
the aggressive build-out for cloud computing. Big data and machine learning applications that perform
tasks such as fraud and intrusion detection, trend detection, and click-stream and social media
analysis all require forward-thinking solutions and enough compute power to deliver the performance
required in a rapidly evolving digital marketplace. Companies increasingly need to drive the speed of
business up, and organizations need to support their customers with real-time data. The task of
managing sensitive information while capturing, analyzing, and acting upon massive volumes of data
every hour of every day has become critical.
These challenges have dramatically changed the way that IT systems are architected, provisioned,
and run compared to the past few decades. Most companies

DevOps cuts deep and wide through industries, company sizes, and technology environments. Yet, DevOps is never done — it’s about continual learning and improvement rather than an end state.
Puppet is here to help. We draw on the success stories and lessons learned at organizations that are already driving improved performance and better business outcomes with their DevOps initiatives.
This handbook captures five essential phases for mapping out a DevOps journey:
1. Build the business case for DevOps.
2. Address the biggest challenges to DevOps success.
3. Develop a performance-driven team structure.
4. Choose the right Tools and processes.
5. Plan your key implementation phases.

The Forrester Study on cost savings and business benefits enabled by Watson Studio and Watson Knowledge Catalog.
Watson Studio provides a suite of tools for data scientists, application developers, and subject matter experts to collaboratively and easily work with data and use that data to build, train and deploy machine learning models at scale. The Forrester provides readers a framework to evaluate the potential financial impact of the Watson Studio and Watson Knowledge Catalog investment on their organizations.

Massive amounts of data are being created driven by
billions of sensors all around us such as cameras, smart
phones, cars as well as the large amounts of data across
enterprises, education systems and organizations. In
the age of big data, artificial intelligence (AI), machine
learning and deep learning deliver unprecedented
insights in the massive amounts of data.
Amazon CEO Jeff Bezos spoke about the potential of
artificial intelligence and machine learning at the 2017
Internet Association‘s annual gala in Washington, D.C.,
“It is a renaissance, it is a golden age,” Bezos said.
“We are solving problems with machine learning and
artificial intelligence that were in the realm of science
fiction for the last several decades. Natural language
understanding, machine vision problems, it really is
an amazing renaissance.” Machine learning and AI is a
horizontal enabling layer. It will empower and improve
every business, every government organization, every
philanthropy

Effective metrics and measurements are critical to running a high performance business. Properly applied, they lead you to better insights, better decisions and better business outcomes. They provide feedback to spark improvement and create learning opportunities. They help you identify the right outcomes that drive you toward your business goals. Unfortunately, many businesses misuse these powerful tools in ways that actively destroy the agility they seek to create. In this paper, we highlight nine mistakes organizations make involving agile measurement at enterprise scale—and how to do it right.

"In today’s IT infrastructure, data security can no longer be treated as an afterthought, because billions of dollars are lost each year to computer intrusions and data exposures. This issue is compounded by the aggressive build-out for cloud computing. Big data and machine learning applications that perform tasks such as fraud and intrusion detection, trend detection, and click-stream and social media analysis all require forward-thinking solutions and enough compute power to deliver the performance required in a rapidly evolving digital marketplace.
Companies increasingly need to drive the speed of business up, and organizations need to support their customers with real-time data. The task of managing sensitive information while capturing, analyzing, and acting upon massive volumes of data every hour of every day has become critical.

Millennials are the first true “digital natives,” and because of this, they are often associated with driving new work practices and expectations. However, it is actually the ubiquity of technology, the accelerated pace of work and our consumer experiences that are driving new work practices, not millennials. New research tells us that to be engaging, L&D teams need to focus on modern learning rather than millennials.The formula for modern learning is:
• Learner-centric
• Micro/modular
• Varied treatments
• Retention-driven
• Embedded
• Mobile
Download “Millennial Learning Myths and Misconceptions Prescriptions for a Modern Learning Strategy” for tips for enabling modern learning at your organization.

An introductory guide on how to use learning to catapult your customer experience to excellence.
Get tips on how to apply learning at every phase of the customer life cycle, the benefits you'll gain, and examples of how leading organizations are putting external learning into practice.

An introductory guide on how to use learning to catapult your customer experience to excellence.
Get tips on how to apply learning at every phase of the customer life cycle, the benefits you'll gain, and examples of how leading organizations are putting external learning into practice.